使用咖啡环效应和卷积神经网络检测牛奶造
Tapan Parsain1, Ajay Tripathi2, Archana Tiwari1
1Department of Physics, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, India.
概括
这项研究引入了一种低成本的咖啡环模式方法,用于检测牛奶中的水和合成牛奶造. 该技术可以准确地区分纯牛奶和造牛奶,提供可靠的检测方法.
科学领域:
- 食品科学 食品科学 食品科学
- 分析化学 分析化学
- 生物物理学的生物物理.
背景情况:
- 牛奶造是影响食品安全和消费者信任的全球性问题.
- 目前的检测方法可能昂贵且耗时.
- 需要一种简单,具有成本效益的方法来检测牛奶造.
研究的目的:
- 开发和验证一种低成本的方法来识别牛奶中的水和合成牛奶造.
- 为了分析由牛奶滴形成的咖啡环图案.
- 用图像分析和机器学习来分类不同类型的伪造剂.
主要方法:
- 牛奶样本被污染了自来水 (TW),蒸水 (DW),矿泉水 (MW) 和合成牛奶.
- 滴滴在玻璃幻灯片上投放,以形成咖啡环图案.
- 测量了环面积,粒子面积和粒子直径.
- 亚历克斯网模型被用来对杂质进行分类.
主要成果:
- 总颗粒面积与总环面积的比率遵循了一个指数模型,平均颗粒径,区分水类.
- 与自来水相比,蒸水和矿泉水 adulterated 牛奶显示出明显的集群.
- 合成牛奶的造导致了独特的图案,如同心圆环和油球.
- 亚历克斯网模型实现了高精度 (96.7%的二进制,95.8%的三进制分类).
结论:
- 咖啡环图案提供了一种可行的,低成本的方法来检测牛奶造.
- 该方法可以有效地区分合成牛奶和纯牛奶.
- 它还可以区分用于伪造的水类型.
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